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J Expo Anal Environ Epidemiol. 1993 Jul-Sep;3(3):259-76.

Why dose-response relationships are often non-linear and some consequences.

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Epidemiology and Health Services Evaluation Unit, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel.


Given the dependence of many risk assessments on the assumption of linearity of dose-response relationships in human populations, we analyze the circumstances likely to lead to non-linearity and test our hypothesis of the high prevalence of non-linearity by examination of recent literature.


The analysis of Bross, based on whether irradiated cells die or can manifest malignancy, leads him to generalize that if a single exposure can have one of two (or more) countervailing outcomes, non-linearity of dose-response will result. We list four other common mechanisms which would have similar effects: symptom-stimulated withdrawal from exposures to respiratory irritants; certain aspects of the "healthy worker effect" (especially its obverse-withdrawal from the work force due to illness); selected consequences of the competing risks of long-term disease; and shift in relative strength among multiple independent variables. We then examine recent literature to see how often reports of linear, monotonic, and non-monotonic dose-response relationships occur and discuss the likelihood of countervailing alternate outcomes in selected examples.


Non-linear and linear relationships are about equally frequent. Under circumstances where countervailing outcomes are probable, dose-response relationships should be non-linear and often are. These conditions may also lead to non-linear difference equations, which may manifest "chaotic" attributes.


Regulations and policies cannot be routinely derived on the basis of extrapolating linear dose-response relationships for human populations. Although our analysis is oriented principally to epidemiology, similar considerations apply to toxicological studies as well.

[Indexed for MEDLINE]

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